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DataONE: A Data Federation with Provenance Support

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Provenance and Annotation of Data and Processes (IPAW 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9672))

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Abstract

DataONE is a federated data network focusing on earth and environmental science data. We present the provenance and search features of DataONE by means of an example involving three earth scientists who interact through a DataONE Member Node. DataONE provenance systems enable reproducible research and facilitate proper attribution of scientific results transitively across generations of derived data products.

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References

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Author information

Authors and Affiliations

  1. University of Illinois, Urbana-Champaign, Illinois, USA

    Yang Cao, Bertram Ludäscher & Timothy McPhillips

  2. National Center for Ecological Analysis and Synthesis, UCSB, Santa Barbara, USA

    Christopher Jones, Matthew B. Jones, Peter Slaughter & Lauren Walker

  3. Universidad Popular Autónoma del Estado de Puebla, Puebla, Mexico

    Víctor Cuevas-Vicenttín

  4. School of Computing Science, Newcastle University, Newcastle upon Tyne, UK

    Paolo Missier

  5. Woods Hole Research Center, Falmouth, Massachusetts, USA

    Christopher Schwalm

  6. University of Kansas, Lawrence, USA

    Dave Vieglais

  7. Environmental Sciences Division, ORNL, Oak Ridge, Tennessee, USA

    Yaxing Wei

Authors
  1. Yang Cao
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  2. Christopher Jones
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  3. Víctor Cuevas-Vicenttín
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  4. Matthew B. Jones
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  5. Bertram Ludäscher
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  6. Timothy McPhillips
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  7. Paolo Missier
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  8. Christopher Schwalm
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  9. Peter Slaughter
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  10. Dave Vieglais
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  11. Lauren Walker
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  12. Yaxing Wei
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Corresponding author

Correspondence to Yang Cao .

Editor information

Editors and Affiliations

  1. COPPE/UFRJ, Rio de Janeiro, Brazil

    Marta Mattoso

  2. Illinois Institute of Technology, Chicago, Illinois, USA

    Boris Glavic

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© 2016 Springer International Publishing Switzerland

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Cao, Y. et al. (2016). DataONE: A Data Federation with Provenance Support. In: Mattoso, M., Glavic, B. (eds) Provenance and Annotation of Data and Processes. IPAW 2016. Lecture Notes in Computer Science(), vol 9672. Springer, Cham. https://doi.org/10.1007/978-3-319-40593-3_28

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  • DOI: https://doi.org/10.1007/978-3-319-40593-3_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40592-6

  • Online ISBN: 978-3-319-40593-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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